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Speech enhancement in noisy environments for video retrieval. / Zhou, Huiyu; Sadka, Abdul
; Jiang, Richard M. 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services. IEEE, 2008. p. 197-200 4556918 (WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services).
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Zhou, H, Sadka, A
& Jiang, RM 2008,
Speech enhancement in noisy environments for video retrieval. in
2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services., 4556918, WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services, IEEE, pp. 197-200, 9th International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS 2008, Klagenfurt, Austria,
7/05/08.
https://doi.org/10.1109/WIAMIS.2008.38APA
Vancouver
Zhou H, Sadka A
, Jiang RM.
Speech enhancement in noisy environments for video retrieval. In 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services. IEEE. 2008. p. 197-200. 4556918. (WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services). doi: 10.1109/WIAMIS.2008.38
Author
Bibtex
@inproceedings{db1c96076151447bb1e28b19edc50b0c,
title = "Speech enhancement in noisy environments for video retrieval",
abstract = "In this paper, we propose a novel spectral subtraction approach for speech enhancement via maximum likelihood estimate (MLE). This scheme attempts to simulate the probability distribution of useful speech signals and hence maximally reduce the noise. To evaluate the quality of speech enhancement, we extract cepstral features from the enhanced signals, and then apply them to a dynamic time warping framework for similarity check between the clean and filtered signals. The performance of the proposed enhancement method is compared to that of other classical techniques. The entire framework does not assume any model for the background noise and does not require any noise training data.",
author = "Huiyu Zhou and Abdul Sadka and Jiang, {Richard M.}",
year = "2008",
month = sep,
day = "19",
doi = "10.1109/WIAMIS.2008.38",
language = "English",
isbn = "9780769531304",
series = "WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services",
publisher = "IEEE",
pages = "197--200",
booktitle = "2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services",
note = "9th International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS 2008 ; Conference date: 07-05-2008 Through 09-05-2008",
}
RIS
TY - GEN
T1 - Speech enhancement in noisy environments for video retrieval
AU - Zhou, Huiyu
AU - Sadka, Abdul
AU - Jiang, Richard M.
PY - 2008/9/19
Y1 - 2008/9/19
N2 - In this paper, we propose a novel spectral subtraction approach for speech enhancement via maximum likelihood estimate (MLE). This scheme attempts to simulate the probability distribution of useful speech signals and hence maximally reduce the noise. To evaluate the quality of speech enhancement, we extract cepstral features from the enhanced signals, and then apply them to a dynamic time warping framework for similarity check between the clean and filtered signals. The performance of the proposed enhancement method is compared to that of other classical techniques. The entire framework does not assume any model for the background noise and does not require any noise training data.
AB - In this paper, we propose a novel spectral subtraction approach for speech enhancement via maximum likelihood estimate (MLE). This scheme attempts to simulate the probability distribution of useful speech signals and hence maximally reduce the noise. To evaluate the quality of speech enhancement, we extract cepstral features from the enhanced signals, and then apply them to a dynamic time warping framework for similarity check between the clean and filtered signals. The performance of the proposed enhancement method is compared to that of other classical techniques. The entire framework does not assume any model for the background noise and does not require any noise training data.
U2 - 10.1109/WIAMIS.2008.38
DO - 10.1109/WIAMIS.2008.38
M3 - Conference contribution/Paper
AN - SCOPUS:51749122483
SN - 9780769531304
T3 - WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services
SP - 197
EP - 200
BT - 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services
PB - IEEE
T2 - 9th International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS 2008
Y2 - 7 May 2008 through 9 May 2008
ER -
